August 3, 2022

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Augmented reality (AR) and artificial intelligence (AI) are two of the most promising technologies available to mobile app developers. Huge hype cycles and rapidly evolving tools, though, have blurred the lines between the two, making it difficult to tell where AI ends and AR begins. This post aims to disambiguate AR and AI. It covers how AR and AI work together, the current state of SDKs and APIs for each, and some practical ways to combine them to build incredible mobile experiences.

Augmented Reality | Launch Trend

Augmented reality is an experience that blends physical and digital environments. Think Pokemon Go or Snapchat. Computer-generated objects coexist and interact with the real world in a single, immersive scene. This is made possible by fusing data from multiple sensors — camera(s), gyroscopes, accelerometers, GPS, etc. — to form a digital representation of the world that can be overlaid on top of the physical one.

Artificial Intelligence | Launch Trend

Artificial intelligence (and more precisely machine and deep learning) includes algorithms and statistical models capable of performing tasks without explicit instructions. Machine learning models are shown training data from which they learn patterns and correlations that help them achieve their goals. These models are the engines inside things like predictive keyboards and intelligent photo organizers.

Augmented reality and artificial intelligence are distinct technologies, but they can be used together to create unique experiences.

In augmented reality, a 3D representation of the world must be constructed to allow digital objects to exist alongside physical ones. Visual data is used along with an accelerometer and gyroscopes to build a map of the world and track movement within it. Most of these tasks are still done using traditional computer vision techniques that make no use of machine learning.

Independently, however, AI models have gotten incredibly good at doing many of the things required to build immersive AR experiences. Deep neural networks can detect vertical and horizontal planes, estimate depth and segment images for realistic occlusion, and even infer 3D positions of objects in real-time. Because of these abilities, AI models are replacing some of the more traditional computer vision approaches underpinning AR experiences.